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Tuhfe Göçmen is a prominent researcher specializing in the field of wind energy systems, focusing on data-driven design optimization and control for wind power plants. He has supervised various PhD students and led multiple projects aimed at enhancing the operational efficiency of wind farms through advanced control systems, including reinforcement learning techniques. His recent projects include ‘Data-driven design optimization control wind power plants’ and ‘Integrated, Value-based Multi-objective wind farm control powered by Artificial Intelligence.’ Göçmen is actively involved in research that aligns with the UN Sustainable Development Goals, contributing significantly to both academic and applied aspects of sustainable energy. His expertise encompasses the development of autonomous data-driven control systems and multi-agent reinforcement learning algorithms for optimal wind farm operations.
Technical University of Denmark • Roskilde, Denmark
Leading research projects on wind farm control and optimization at the Department of Electrical Engineering.
This requirement applies generally across Technical University of Denmark (DTU) MSc programs including Computer Science, Applied Mathematics, and Engineering disciplines. Specific prerequisites vary by department/curriculum.